Computational protein design with backbone plasticity

The computational algorithms used in the design of artificial proteins have become increasingly sophisticated in recent years, producing a series of remarkable successes. The most dramatic of these is the de novo design of artificial enzymes. The majority of these designs have reused naturally occurring protein structures as “scaffolds” onto which novel functionality can be grafted without having to redesign the backbone structure. The incorporation of backbone flexibility into protein design is a much more computationally challenging problem due to the greatly increase search space but promises to remove the limitations of reusing natural protein scaffolds. In this review, we outline the principles of computational protein design methods and discuss recent efforts to consider backbone plasticity in the design process

Computational Protein Design Using AND/OR Branch-and-Bound Search

The computation of the global minimum energy conformation (GMEC) is an important and challenging topic in structure-based computational protein design. In this paper, we propose a new protein design algorithm based on the AND/OR branch-and-bound (AOBB) search, which is a variant of the traditional branch-and-bound search algorithm, to solve this combinatorial optimization problem. By integrating with a powerful heuristic function, AOBB is able to fully exploit the graph structure of the underlying residue interaction network of a backbone template to significantly accelerate the design process. Tests on real protein data show that our new protein design algorithm is able to solve many prob- lems that were previously unsolvable by the traditional exact search algorithms, and for the problems that can be solved with traditional provable algorithms, our new method can provide a large speedup by several orders of magnitude while still guaranteeing to find the global minimum energy conformation (GMEC) solution.Comment: RECOMB 201

Strategies for synthesis of yardsticks and abaci for nanometre distance measurements by pulsed EPR

Silvia Valera is grateful for support by EPSRC and Bela E. Bode acknowledges support by EastCHEM.Pulsed electron paramagnetic resonance (EPR) techniques have been found to be an efficient tool for elucidation of structure in complex biological systems as they give access to distances in the nanometre range. These measurements can provide additional structural information such as relative orientations, structural flexibility or aggregation states. A wide variety of model systems for calibration and optimisation of pulsed experiments has been synthesised. Their design is based on mimicking biological systems or materials in specific properties such as the distances themselves and the distance distributions. Here, we review selected approaches to the synthesis of chemical systems bearing two or more spin centres, such as nitroxide or trityl radicals, metal ions or combinations thereof and sketch their application in pulsed EPR distance measurements.Publisher PDFPeer reviewe

De novo backbone and sequence design of an idealized α/β-barrel protein: evidence of stable tertiary structure

We have designed, synthesized, and characterized a 216 amino acid residue sequence encoding a putative idealized α/β-barrel protein. The design was elaborated in two steps. First, the idealized backbone was defined with geometric parameters representing our target fold: a central eight parallel-stranded β-sheet surrounded by eight parallel α-helices, connected together with short structural turns on both sides of the barrel. An automated sequence selection algorithm, based on the dead-end elimination theorem, was used to find the optimal amino acid sequence fitting the target structure. A synthetic gene coding for the designed sequence was constructed and the recombinant artificial protein was expressed in bacteria, purified and characterized. Far-UV CD spectra with prominent bands at 222 nm and 208 nm revealed the presence of α-helix secondary structures (50%) in fairly good agreement with the model. A pronounced absorption band in the near-UV CD region, arising from immobilized aromatic side-chains, showed that the artificial protein is folded in solution. Chemical unfolding monitored by tryptophan fluorescence revealed a conformational stability (ΔGH_2O) of 35 kJ/mol. Thermal unfolding monitored by near-UV CD revealed a cooperative transition with an apparent T_m of 65 °C. Moreover, the artificial protein did not exhibit any affinity for the hydrophobic fluorescent probe 1-anilinonaphthalene-8-sulfonic acid (ANS), providing additional evidence that the artificial barrel is not in the molten globule state, contrary to previously designed artificial a/ b-barrels. Finally, ^1H NMR spectra of the folded and unfolded proteins provided evidence for specific interactions in the folded protein. Taken together, the results indicate that the de novo designed α/β-barrel protein adopts a stable three-dimensional structure in solution. These encouraging results show that de novo design of an idealized protein structure of more than 200 amino acid residues is now possible, from construction of a particular backbone conformation to determination of an amino acid sequence with an automated sequence selection algorithm

Flat-Bottom Strategy for Improved Accuracy in Protein Side-Chain Placements

We present a new strategy for protein side-chain placement that uses flat-bottom potentials for rotamer scoring. The extent of the flat bottom depends on the coarseness of the rotamer library and is optimized for libraries ranging from diversities of 0.2 Å to 5.0 Å. The parameters reported here were optimized for forcefields using Lennard-Jones 12−6 van der Waals potential with DREIDING parameters but are expected to be similar for AMBER, CHARMM, and other forcefields. This Side-Chain Rotamer Excitation Analysis Method is implemented in the SCREAM software package. Similar scoring function strategies should be useful for ligand docking, virtual ligand screening, and protein folding applications

Protein Design Using Continuous Rotamers

Optimizing amino acid conformation and identity is a central problem in computational protein design. Protein design algorithms must allow realistic protein flexibility to occur during this optimization, or they may fail to find the best sequence with the lowest energy. Most design algorithms implement side-chain flexibility by allowing the side chains to move between a small set of discrete, low-energy states, which we call rigid rotamers. In this work we show that allowing continuous side-chain flexibility (which we call continuous rotamers) greatly improves protein flexibility modeling. We present a large-scale study that compares the sequences and best energy conformations in 69 protein-core redesigns using a rigid-rotamer model versus a continuous-rotamer model. We show that in nearly all of our redesigns the sequence found by the continuous-rotamer model is different and has a lower energy than the one found by the rigid-rotamer model. Moreover, the sequences found by the continuous-rotamer model are more similar to the native sequences. We then show that the seemingly easy solution of sampling more rigid rotamers within the continuous region is not a practical alternative to a continuous-rotamer model: at computationally feasible resolutions, using more rigid rotamers was never better than a continuous-rotamer model and almost always resulted in higher energies. Finally, we present a new protein design algorithm based on the dead-end elimination (DEE) algorithm, which we call iMinDEE, that makes the use of continuous rotamers feasible in larger systems. iMinDEE guarantees finding the optimal answer while pruning the search space with close to the same efficiency of DEE. Availability: Software is available under the Lesser GNU Public License v3. Contact the authors for source code

Cost Function Networks to Solve Large Computational Protein Design Problems

International audienc

Predicting the Tolerated Sequences for Proteins and Protein Interfaces Using RosettaBackrub Flexible Backbone Design

Predicting the set of sequences that are tolerated by a protein or protein interface, while maintaining a desired function, is useful for characterizing protein interaction specificity and for computationally designing sequence libraries to engineer proteins with new functions. Here we provide a general method, a detailed set of protocols, and several benchmarks and analyses for estimating tolerated sequences using flexible backbone protein design implemented in the Rosetta molecular modeling software suite. The input to the method is at least one experimentally determined three-dimensional protein structure or high-quality model. The starting structure(s) are expanded or refined into a conformational ensemble using Monte Carlo simulations consisting of backrub backbone and side chain moves in Rosetta. The method then uses a combination of simulated annealing and genetic algorithm optimization methods to enrich for low-energy sequences for the individual members of the ensemble. To emphasize certain functional requirements (e.g. forming a binding interface), interactions between and within parts of the structure (e.g. domains) can be reweighted in the scoring function. Results from each backbone structure are merged together to create a single estimate for the tolerated sequence space. We provide an extensive description of the protocol and its parameters, all source code, example analysis scripts and three tests applying this method to finding sequences predicted to stabilize proteins or protein interfaces. The generality of this method makes many other applications possible, for example stabilizing interactions with small molecules, DNA, or RNA. Through the use of within-domain reweighting and/or multistate design, it may also be possible to use this method to find sequences that stabilize particular protein conformations or binding interactions over others